General discrete choice model and optimization algorithm for revenue management

Abstract

A discrete choice model of consumer demand is employed to generate controls to limit or open up availability of inventory of a resource, for example, thereby improving the revenue of a firm offering the resource for sale. The consumer's choice process is modeled as a set of choice probabilities that depend on what alternatives are available at that moment. An optimization algorithm is preferably employed for determining what choices to offer for sale at any point of time in a pricing or revenue management system. An estimation algorithm that is preferably used with the choice model for estimating the size of the potential customer base and estimating the price and product attribute value sensitivity of customers based solely on historical and transactional data (hypothesizing as unobservable, customer no-purchases).

1 . A computer implemented revenue management method for managing allocation of a resource, comprising the steps of: 
 a) providing a discrete choice model of consumer demand which models consumer preferences for a plurality of units of a resource based on known information, including historical choices and information relating to attributes of said units,    b) generating a plurality of control values using said model; and    c) applying said control values to a resource management controlling system which, using said values, defines a set of choices of said units to be offered for sale to consumers and attributes of said units.    
     
     
         2 . The method of  claim 1 , wherein said step of generating a plurality of control values further includes the steps of estimating non-observable no-purchase data from said known information, and correcting for said non-observable no-purchase data in said model prior to generating said control values.  
     
     
         3 . The method of  claim 2 , wherein said step of generating a plurality of control values further includes applying an optimization algorithm to said control values to generate optimized control values.  
     
     
         4 . The method of  claim 1 , wherein said step of generating a plurality of control values further includes applying an optimization algorithm to said control values to generate optimize d control values.  
     
     
         5 . The method of  claim 1 , wherein said resource comprises an item selected from the group comprising seats on a means of transportation for a trip to a selected destination, cargo space on a means of transportation for a trip to a selected destination, advertising time slots, tickets to facilities for at least one scheduled event, tickets to facilities for the resources of a manufacturing facility, products sold at a retail location or via electronic commerce, and energy products.  
     
     
         6 . A computer implemented method for managing pricing of a resource, comprising the steps of: 
 a) providing a discrete choice model of consumer demand which models consumer preferences for a plurality of units of a resource based on known information, including historical choices and information relating to attributes of said units, said attributes including price of said units;    b) estimating non-observable no-purchase data from said known information; and    c) generating price/demand relationships using said model and correcting for said non-observable no-purchase data.    
     
     
         7 . The method of  claim 6 , wherein said resource comprises an item selected from the group comprising seats on a means of transportation for a trip to a selected destination, cargo space on a means of transportation for a trip to a selected destination, advertising time slots, tickets to facilities for at least one scheduled event, tickets to facilities for the resources of a manufacturing facility, products sold at a retail location or via electronic commerce, and energy products.